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The best case scenario would seem to be that results are derived from certain biases built into the model, unless it weighs “factuality” by the number of occurrences of certain statements on the internet which is as far from a qualification for truthfulness as the biased model.
IMVHO people do not need "automated fact verification" as a source of trust we can't trust, but summarizers: most FLOSS users and not so few computer users in the largest sense do use feeds, but they got many posts per day and some days they like to read them all, some others they are busy. Tools to skim news and offer a sort of index to decide what to see, a kind of smart scoring is much more interesting.
The idea that "specificity," such as what scientific research aims for, can be better evaluated for truthfulness or approach what "truly matters," as this project purports, is dubious. E.g., why would a notion that is more limited in scope matter more than something more vast (to use the word that it cites as an example)? In addition to its dystopian idea of a "source of truth," it completely dismisses "vague" language in the name of "science" or "factuality," which is utterly the opposite of science, which I thought was to understand ourselves and nature with as few presuppositions as possible.
How does AI observe facts in real world? I find hilarious clarify something as fact checkig based on data on internet.